Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)
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Updated
Apr 26, 2021 - Jupyter Notebook
Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)
Code to reproduce analysis from "Dealing with area-to-point spatial misalignment in species distribution models" published in Ecography.
Snapshot of Toulouse public library customer habits (Médiathèque José Cabanis) — cleaning messy datasets of musical, cinematic, and literary checkouts; includes data-cleaning steps, analysis notebook revealing cultural tastes in the Pink City.
📚 Explore the Toulouse public library dataset, a rich tapestry of community stories woven through its catalog of borrowed books and forgotten titles.
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